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"""

Single-axis tracking

====================

Examples of modeling tilt angles for single-axis tracker arrays.

"""

#%%

# This example shows basic usage of pvlib's tracker position calculations with

# :py:meth:`pvlib.tracking.singleaxis`. The examples shown here demonstrate

# how the tracker parameters affect the generated tilt angles.

#

# Because tracker angle is based on where the sun is in the sky, calculating

# solar position is always the first step.

#

# True-tracking

# -------------

#

# The basic tracking algorithm is called "true-tracking". It orients the panels

# towards the sun as much as possible in order to maximize the cross section

# presented towards incoming beam irradiance.

from pvlib import solarposition, tracking

import pandas as pd

import matplotlib.pyplot as plt

tz = 'US/Eastern'

lat, lon = 40, -80

times = pd.date_range('2019-01-01', '2019-01-02', closed='left', freq='5min',

tz=tz)

solpos = solarposition.get_solarposition(times, lat, lon)

truetracking_angles = tracking.singleaxis(

apparent_zenith=solpos['apparent_zenith'],

apparent_azimuth=solpos['azimuth'],

axis_tilt=0,

axis_azimuth=180,

max_angle=90,

backtrack=False, # for true-tracking

gcr=0.5) # irrelevant for true-tracking

truetracking_position = truetracking_angles['tracker_theta'].fillna(0)

truetracking_position.plot(title='Truetracking Curve')

plt.show()

#%%

# Backtracking

# -------------

#

# Because truetracking yields steep tilt angle in morning and afternoon, it

# will cause row to row shading as the shadows from adjacent rows fall on each

# other. To prevent this, the trackers can rotate backwards when the sun is

# near the horizon -- "backtracking". The shading angle depends on row

# geometry, so the gcr parameter must be specified. The greater the gcr, the

# tighter the row spacing and the more aggressively the array must backtrack.

fig, ax = plt.subplots()

for gcr in [0.2, 0.4, 0.6]:

backtracking_angles = tracking.singleaxis(

apparent_zenith=solpos['apparent_zenith'],

apparent_azimuth=solpos['azimuth'],

axis_tilt=0,

axis_azimuth=180,

max_angle=90,

backtrack=True,

gcr=gcr)

backtracking_position = backtracking_angles['tracker_theta'].fillna(0)

backtracking_position.plot(title='Backtracking Curve',

label=f'GCR:{gcr:0.01f}',

ax=ax)

plt.legend()

plt.show()